The longest imaginable

Calculus Level 4

Evaluate lim n 0 1 0 1 0 1 n x 1 + x 2 + + x n d x 1 d x 2 d x n . \lim_{n \to \infty} \displaystyle \int_0^1 \int_0^1 \ldots \int_0^1 \dfrac{n}{x_1+x_2+\dots+x_n}\, dx_1 dx_2 \ldots dx_n.

Clarification: In the answer options, e ( 2.71828 ) e \, (\approx 2.71828) is the Euler's number .


Note: This problem is a generalization of my previous problem .
1 2 3 e e The limit diverges

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2 solutions

Efren Medallo
Jun 8, 2017

This may not be the first time for you to see this solution.

First, we note of this integral

0 e a x d x = 1 a \displaystyle \int_0^{\infty} e^{-ax} \mathrm{d}x = \frac{1}{a}

We can actually use this to our advantage, to transform the integrand in question, to an integral wrt to a dummy variable t t , that is

n x 1 + x 2 + x 3 + + x n = 0 e x 1 + x 2 + + x n n t d t \dfrac{n}{x_1 + x_2 + x_3 + \dots + x_n} = \displaystyle\int_0^{\infty} e^{ - \frac{x_1+x_2+\dots+x_n}{n}t} \mathrm{d}t

Plugging this into the equation, we will get

0 1 0 1 d x 1 d x 2 d x 3 d x n 0 e x 1 + x 2 + + x n n t d t \displaystyle \int_0^1 \dots \int_0^1 \mathrm{d}x_1\mathrm{d}x_2 \mathrm{d}x_3\dots \mathrm{d}x_n \int_0^{\infty} e^{ -\frac{x_1+x_2+\dots+x_n}{n}t} \mathrm{d}t

And changing the order of integration, we'll get this

lim n 0 ( 0 1 e x n t d x ) n d t \lim\limits_{n\to \infty} \displaystyle \int_0^{\infty} \bigg( \int_0^1 e^{-\frac{x}{n} t} \mathrm{d}x \bigg)^n \mathrm{d}t

lim n 0 ( 1 e t / n t / n ) n d t \lim\limits_{n \to \infty} \displaystyle \int_0^{\infty} \bigg( \frac{ 1 - e^{ -t/n}}{t/n} \bigg)^n \mathrm{d}t

0 lim n ( 1 e t / n t / n ) n d t \displaystyle \int_0^{\infty} \lim\limits_{n \to \infty} \bigg( \frac{ 1 - e^{ -t/n}}{t/n} \bigg)^n \mathrm{d}t

0 e t / 2 lim n ( e t / 2 n + e t / 2 n t / n ) n d t \displaystyle \int_0^{\infty} e^{-t/2} \lim\limits_{n \to \infty} \bigg( \frac{ e^{ t/2n} + e^{-t/2n}}{t/n} \bigg)^n \mathrm{d}t

0 e t / 2 lim n ( 2 sinh ( t / 2 n ) t / n ) n d t \displaystyle \int_0^{\infty} e^{-t/2} \lim\limits_{n \to \infty} \bigg( \frac{2 \sinh (t/2n)}{t/n} \bigg)^n \mathrm{d}t

0 e t / 2 lim n ( sinh ( t / 2 n ) t / 2 n ) n d t \displaystyle \int_0^{\infty} e^{-t/2} \lim\limits_{n \to \infty} \bigg( \frac{ \sinh(t/2n)}{t/2n} \bigg)^n \mathrm{d}t

Now, note that lim k 0 sinh k x k x = 1 \lim_{k\to 0} \frac{\sinh kx}{kx} = 1

This simplifies our integral to

0 e t / 2 d t = 2 \displaystyle \int_0^{\infty} e^{-t/2} \mathrm{d}t = 2 . (See edit below)

Edit: to justify for the said limit, we will isolate it first and solve it by means of L'Hopital's rule. First we let u = t 2 u = \frac{t}{2} .

A = lim n [ sinh ( u / n ) u / n ] n A = \lim\limits_{n \to \infty} \bigg[ \frac{ \sinh(u/n)}{ u/n} \bigg]^n

Since A is of the indeterminate form 1 1^{\infty} , we need to transform it to a form where L'Hopital's rule can be used.

ln A = lim n n ln [ sinh ( u / n ) u / n ] \ln A = \lim\limits_{n \to \infty} n \ln \bigg[ \frac{ \sinh(u/n)}{u/n} \bigg]

This is now of the form 0 0 \cdot \infty . A little more modification will lead us to

ln A = lim n ln ( sinh ( u / n ) u / n ) 1 n \ln A = \lim\limits_{n \to \infty} \dfrac{ \ln \bigg( \frac{\sinh(u/n)}{u/n} \bigg) }{ \frac{1}{n}}

This can now be evaluated via L'hopital's rule. Differentiating both the numerator and the denominator twice wrt n n , we will get

ln A = lim n n 3 [ u 2 csch 2 ( u / n ) 2 u n coth ( u / n ) + n 2 ] n 4 \ln A = \lim\limits_{n \to \infty} \dfrac{ n^3 [ u^2 \text{csch}^2 (u/n) - 2un \coth(u/n) +n^2] }{n^4}

This will evaluate to zero.

Going back now, we can say that A = e 0 = 1 A = e^0 = 1 .

Your proof needs a little more detail. At about the third line, you state that lim n 0 ( 1 e t / n t / n ) n d t = 0 lim n ( 1 e t / n t / n ) n d t \lim_{n \to \infty}\int_0^\infty \left(\frac{1 - e^{-t/n}}{t/n}\right)^n\,dt \; =\; \int_0^\infty \lim_{n \to \infty} \left(\frac{1 - e^{-t/n}}{t/n}\right)^n\,dt It is not necessarily true that the limit of a sequence of integrals is the integral of the limit function - consider for example the integrals 0 1 n x n d x \int_0^1 nx^n\,dx ; the integrand tends to 0 0 for 0 < x < 1 0 < x < 1 , but the integrals tend to 1 1 .

What makes this argument work is that ( sinh t / n t / n ) n \left(\frac{\sinh t/n}{t/n}\right)^n tends monotonically (decreasingly) to 1 1 as n n \to \infty for all t > 0 t > 0 . We can then use the Monotone Convergence Theorem to deduce that the limit of the integrals is the integral of the limit.

Mark Hennings - 4 years ago

I know that lim k 0 sinh ( k x ) k x = 1 \lim_{k \rightarrow 0} \frac{\sinh(kx)} {kx} = 1 , but since this is to the n n -th power and n n is approaching infinity, the explanation is not so simple.

Guilherme Niedu - 4 years ago

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I have edited the solution to justify for said limit :)

Efren Medallo - 4 years ago

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Thanks, now it is perfect!

Guilherme Niedu - 4 years ago

When I got to what is your fifth line I tried using binomial theorem and failed. Do you think this way would have worked?

First Last - 4 years ago

As n gets large, most of the region of integration (a high-dimensional cube) is close to the hyperplane joining the vertices where the sum of the xi is n/2 (if n is even) or (n+1)/2 (if n is odd). The integrand is 2 (or tends to 2) on this region so the integral tends to 2×(volume of the hypercube) ie 2.

Tom Richards - 3 years, 11 months ago

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This is a heuristic argument. The limit of 2 2 is reasonable, but analysis requires putting definite controls on quantities like "most of" and the like.

"Most of" the reciprocals 1 / n 1/n are very small, but the sum of all of them diverges, for example.

Mark Hennings - 3 years, 11 months ago
Abhishek Sinha
Aug 5, 2017

Let { X i } i \{X_i\}_{i} be a sequence of i.i.d. random variables each following a uniform distribution in the interval [ 0 , 1 ] [0,1] , with expectation μ = 1 / 2 \mu=1/2 . Then by the Strong Law of Large Numbers , we have almost surely lim n n X 1 + X 2 + + X n 1 μ . \lim_{n \to \infty} \frac{n}{X_1+X_2+\ldots + X_n} \to \frac{1}{\mu}. Then, assuming that the limit and expectation can be exchanged (usually proved by showing that the random sequence is Uniformly Integrable, which I skip), we have lim n E ( n X 1 + X 2 + + X n ) = E ( lim n X 1 + X 2 + + X n ) = 1 μ = 2. \lim_{n} \mathbb{E}(\frac{n}{X_1+X_2+\ldots + X_n} ) = \mathbb{E}(\lim \frac{n}{X_1+X_2+\ldots + X_n} )=\frac{1}{\mu}=2. The proof follows after noting that the LHS is simply the integral in question. \blacksquare

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